Nanoscience Fundamentals Training Course

This practical workshop introduces the core principles of bioinformatics. It is designed for individuals with a foundational background in biology and molecular biology who wish to learn how to process and analyze biological data using computational methods. The program is tailored specifically for:

• Researchers working in experimental laboratories on biological macromolecules: proteins, RNA, and DNA
• Scientists whose primary expertise lies outside of biology but who need to handle biological data
• Managers launching new products (e.g., pharmaceuticals) who seek to expand their understanding of current bioinformatics practices
• Computer programmers planning to develop software applications focused on biological molecules

The curriculum is split into theoretical and practical segments. Lectures are integrated with hands-on exercises, quizzes, and concept checks to ensure participants grasp the key concepts. Throughout the training, participants will follow a guided journey covering all foundational aspects of biological data analysis. This workshop serves as an excellent entry point into bioinformatics, equipping learners to address fundamental bioinformatics challenges: identifying authoritative data sources, extracting relevant information, understanding core algorithms, and confidently using bioinformatics tools.

Upon completion, participants will be capable of utilizing bioinformatics tools to work effectively with biological data.

This instructor-led, live training in Romania (online or onsite) is designed for healthcare professionals and staff who want to gain intermediate to advanced knowledge of various genetic sequencing and testing procedures.

Upon completing this training, participants will be able to:

• Learn and comprehend core genetic concepts.
• Grasp how genetic sequencing and testing operations function.

Good Clinical Practice (GCP) comprises a set of guidelines designed for clinical research involving human subjects. It serves as the international standard for the design, conduct, monitoring, documentation, analysis, and reporting of clinical trials.

In this instructor-led live training, participants will learn the essential guidelines and fundamental principles applied in Good Clinical Practice (GCP) for clinical trials and studies involving human subjects. The course offers an overview of various GCP areas, with a particular emphasis on ICH-centric GCP for Investigational Drugs and Biologics.

By the end of this training, participants will be able to:

• Grasp the fundamental principles of GCP for investigational drugs and biologics, as outlined by the International Conference on Harmonization (ICH)
• Apply GCP guidelines to their clinical research and trials

Audience

• Clinical investigators
• Clinical research professionals
• Healthcare and medical professionals
• Clinical trials support staff
• Research and development staff

Format of the course

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Microbial genomics and metagenomics integrate sequencing technologies with computational analysis to profile microbial communities, characterize genomes, and identify functional traits such as antimicrobial resistance.

This instructor-led live training, available online or onsite, is designed for beginner to intermediate researchers and bioinformaticians seeking hands-on experience with microbial genomics and metagenomic sequencing data analysis.

Upon completing this training, participants will be able to:

• Describe common sequencing workflows and key file formats used in microbial genomics.
• Conduct quality control and preprocessing of raw NGS reads.
• Perform taxonomic profiling using marker-based and k-mer approaches.
• Assemble and annotate microbial genomes and plasmids.
• Detect SNPs, build phylogenetic trees, and interpret population structure.
• Predict antimicrobial resistance genes and summarize functional profiles.
• Utilize reproducible workflows with Conda, Docker, and notebook-based reporting.

Format of the Course

• Lectures introducing concepts and tools (20%).
• Hands-on practical sessions using example datasets (60%).
• Open discussions and guided analysis, allowing participants to apply methods to their own data (20%).

Course Customization Options

• To request a customized workshop focusing on clinical, environmental, or industrial metagenomics, please contact us to arrange.

This is a hands-on course designed to illustrate why programming is a powerful tool in the context of solving biological problems. During the course, participants will learn the Python programming language, widely recognized for its power and ease of use. This course demonstrates how bioinformatics can enhance the daily lives of biologists.

The course is designed for individuals without a computer science background who wish to learn programming.

This course is suitable for:

• Researchers working with biological data.
• Scientists interested in automating routine tasks and analyzing data.
• Managers looking to understand how programming can improve workflows and project execution.

By the end of the course, participants will be able to write short programs to manipulate, analyze, and handle biological data, as well as present results graphically.

This program is designed to equip researchers with a comprehensive understanding of the fundamental principles of statistical design and analysis, highlighting their critical application across diverse scientific fields.

The curriculum introduces key probabilistic and statistical methodologies, primarily illustrated through practical examples. The training structure consists of approximately 30% instructional lectures and 70% guided quizzes and laboratory exercises.

For private or closed courses, we can customize the examples and course materials to align with specific disciplines, such as psychology assessments, public sector applications, biology, or genetics.

In public course settings, a mix of general examples is utilized to ensure broad applicability.

While the course utilizes various software tools ranging from Microsoft Excel to SPSS and Statgraphics, the primary emphasis remains on mastering the conceptual frameworks and processes that drive research, logical reasoning, and data interpretation.

This program is also available in a blended format, incorporating homework assignments and practical tasks to reinforce learning.